I tried looking at what others have done with problem similar to mine, but I still get the same error. I have no idea what's causing it. I've tried following: How to install Theano on Anaconda Python 2.7 x64 on Windows?
but that didn't help.
I'm trying to run this example, but with my own dataset: https://github.com/Lasagne/Lasagne/blob/master/examples/mnist.py
Error message is as follows, I didn't include the 787 other lines inbetween:
C:\Anaconda2\python.exe "C:/Users/mikrolab/Dropbox/Skole UiS/4. semester/Master/Master/hoved/ansiktsgjenkjenning/sklearntest.py" mlp 400
C:\Anaconda2\lib\site-packages\theano-0.8.0-py2.7.egg\theano\tensor\signal\downsample.py:6: UserWarning: downsample module has been moved to the theano.tensor.signal.pool module.
"downsample module has been moved to the theano.tensor.signal.pool module.")
Loading data...
Building model and compiling functions...
WARNING (theano.gof.compilelock): Overriding existing lock by dead process '10436' (I am process '16120')
Problem occurred during compilation with the command line below:
C:\Anaconda2\Scripts\g++.bat -shared -g -O3 -fno-math-errno -Wno-unused-label -Wno-unused-variable -Wno-write-strings -march=core2 -mcx16 -msahf -mno-movbe -mno-aes -mno-pclmul -mno-popcnt -mno-abm -mno-lwp -mno-fma -mno-fma4 -mno-xop -mno-bmi -mno-bmi2 -mno-tbm -mno-avx -mno-avx2 -mno-sse4.2 -msse4.1 -mno-lzcnt --param l1-cache-size=32 --param l1-cache-line-size=64 --param l2-cache-size=6144 -mtune=core2 -DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION -m32 -IC:\Anaconda2\lib\site-packages\numpy\core\include -IC:\Anaconda2\include -IC:\Anaconda2\lib\site-packages\theano-0.8.0-py2.7.egg\theano\gof -o C:\Users\mikrolab\AppData\Local\Theano\compiledir_Windows-10-10.0.10586-Intel64_Family_6_Model_23_Stepping_10_GenuineIntel-2.7.11-32\tmpahcj6d\df1196e30ea06df2bcfcd011958dc6f5.pyd C:\Users\mikrolab\AppData\Local\Theano\compiledir_Windows-10-10.0.10586-Intel64_Family_6_Model_23_Stepping_10_GenuineIntel-2.7.11-32\tmpahcj6d\mod.cpp -LC:\Anaconda2\libs -LC:\Anaconda2 -lpython27
Traceback (most recent call last):
File "C:/Users/mikrolab/Dropbox/Skole UiS/4. semester/Master/Master/hoved/ansiktsgjenkjenning/sklearntest.py", line 312, in <module>
C:\Users\mikrolab\AppData\Local\Theano\compiledir_Windows-10-10.0.10586-Intel64_Family_6_Model_23_Stepping_10_GenuineIntel-2.7.11-32\tmpahcj6d\mod.cpp: In member function 'int {anonymous}::__struct_compiled_op_df1196e30ea06df2bcfcd011958dc6f5::run()':
C:\Users\mikrolab\AppData\Local\Theano\compiledir_Windows-10-10.0.10586-Intel64_Family_6_Model_23_Stepping_10_GenuineIntel-2.7.11-32\tmpahcj6d\mod.cpp:457:34: error: cannot convert 'npy_int64* {aka long long int*}' to 'npy_intp* {aka int*}' in argument passing
main(**kwargs)
File "C:/Users/mikrolab/Dropbox/Skole UiS/4.semester/Master/Master/hoved/ansiktsgjenkjenning/sklearntest.py", line 245, in main
updates = updates)
File "C:\Anaconda2\lib\site-packages\theano-0.8.0-py2.7.egg\theano\compile\function.py", line 322, in function
output_keys=output_keys)
File "C:\Anaconda2\lib\site-packages\theano-0.8.0-py2.7.egg\theano\compile\pfunc.py", line 480, in pfunc
output_keys=output_keys)
File "C:\Anaconda2\lib\site-packages\theano-0.8.0-py2.7.egg\theano\compile\function_module.py", line 1779, in orig_function
defaults)
File "C:\Anaconda2\lib\site-packages\theano-0.8.0-py2.7.egg\theano\compile\function_module.py", line 1643, in create
input_storage=input_storage_lists, storage_map=storage_map)
File "C:\Anaconda2\lib\site-packages\theano-0.8.0-py2.7.egg\theano\gof\link.py", line 690, in make_thunk
storage_map=storage_map)[:3]
File "C:\Anaconda2\lib\site-packages\theano-0.8.0-py2.7.egg\theano\gof\vm.py", line 1005, in make_all
no_recycling))
File "C:\Anaconda2\lib\site-packages\theano-0.8.0-py2.7.egg\theano\gof\op.py", line 978, in make_thunk
no_recycling)
File "C:\Anaconda2\lib\site-packages\theano-0.8.0-py2.7.egg\theano\gof\op.py", line 881, in make_c_thunk
output_storage=node_output_storage)
File "C:\Anaconda2\lib\site-packages\theano-0.8.0-py2.7.egg\theano\gof\cc.py", line 1200, in make_thunk
keep_lock=keep_lock)
File "C:\Anaconda2\lib\site-packages\theano-0.8.0-py2.7.egg\theano\gof\cc.py", line 1143, in compile
keep_lock=keep_lock)
File "C:\Anaconda2\lib\site-packages\theano-0.8.0-py2.7.egg\theano\gof\cc.py", line 1595, in cthunk_factory
key=key, lnk=self, keep_lock=keep_lock)
File "C:\Anaconda2\lib\site-packages\theano-0.8.0-py2.7.egg\theano\gof\cmodule.py", line 1142, in module_from_key
module = lnk.compile_cmodule(location)
File "C:\Anaconda2\lib\site-packages\theano-0.8.0-py2.7.egg\theano\gof\cc.py", line 1506, in compile_cmodule
preargs=preargs)
File "C:\Anaconda2\lib\site-packages\theano-0.8.0-py2.7.egg\theano\gof\cmodule.py", line 2204, in compile_str
(status, compile_stderr.replace('\n', '. ')))
Exception: ('The following error happened while compiling the node', mrg_uniform{TensorType(float32, 4D),inplace}(<TensorType(int32, matrix)>, MakeVector{dtype='int64'}.0), '\n', "Compilation failed (return status=1):
C:\\Users\\mikrolab\\AppData\\Local\\Theano\\compiledir_Windows-10-10.0.10586-Intel64_Family_6_Model_23_Stepping_10_GenuineIntel-2.7.11-32\\tmpahcj6d\\mod.cpp: In member function 'int {anonymous}::__struct_compiled_op_df1196e30ea06df2bcfcd011958dc6f5::run()':\r.
C:\\Users\\mikrolab\\AppData\\Local\\Theano\\compiledir_Windows-10-10.0.10586-Intel64_Family_6_Model_23_Stepping_10_GenuineIntel-2.7.11-32\\tmpahcj6d\\mod.cpp:457:34: error: cannot convert 'npy_int64* {aka long long int*}' to 'npy_intp* {aka int*}' in argument passing\r. ", '[*1 -> mrg_uniform{TensorType(float32, 4D),inplace}(<TensorType(int32, matrix)>, <TensorType(int64, vector)>), *1::1]')
Process finished with exit code 1
Solved: Followed every part of the following instructions: http://deeplearning.net/software/theano/install_windows.html#install-windows
did this as well: Why can't nvcc find my Visual C++ installation?
Theano is working now and is using my GPU.
Use Microsoft Visual Studio 2010 with Anaconda as you have to use the same compiler they used for packages you compile to be compatible. They do have mingw bindings but I'm not sure how compatible they are.